R version 3.2.2 (2015-08-14) -- "Fire Safety"
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Platform: x86_64-pc-linux-gnu (64-bit)

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> x <- c(79.55,80.08,80.15,80.69,81.56,81.23,81.39,81.61,82.25,82.06,82.82,82.3,83.09,83.21,83.13,84.31,83.62,83.75,84.1,83.71,84.2,85.13,86.16,86.65,87.44,87.62,88.03,89.1,89.68,89.47,90.13,89.49,89.52,89.86,89.77,89.8,90.89,90.82,90.68,90.92,90.82,90.09,89.71,89.34,89.2,89.48,89.72,89.58,90.65,90.93,91.42,91.52,91.76,91.47,91.37,91.35,91.74,91.78,91.88,91.99,92.55,92.94,92.81,93.35,93.72,93.94,94.03,93.66,93.78,94.1,94.85,94.83,95.06,95.87,95.97,95.96,96.3,96.17,96.18,96.55,96.76,97.63,97.86,97.82,98.62,99.24,99.63,100.27,100.84,101.05,100.38,100.02,99.97,99.95,100,100.04,100.51,100.29,100.22,101.29,100.29,100.26,100.39,99.3,98.9,98.76,99.12,99.28)
> par8 = ''
> par7 = '0.95'
> par6 = 'White Noise'
> par5 = '12'
> par4 = '0'
> par3 = '1'
> par2 = '1'
> par1 = '48'
> par8 <- ''
> par7 <- '0.95'
> par6 <- 'White Noise'
> par5 <- '12'
> par4 <- '0'
> par3 <- '1'
> par2 <- '1'
> par1 <- '48'
> #'GNU S' R Code compiled by R2WASP v. 1.2.291 ()
> #Author: root
> #To cite this work: Wessa P., (2012), (Partial) Autocorrelation Function (v1.0.11) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_autocorrelation.wasp/
> #Source of accompanying publication: 
> #
> if (par1 == 'Default') {
+ par1 = 10*log10(length(x))
+ } else {
+ par1 <- as.numeric(par1)
+ }
> par2 <- as.numeric(par2)
> par3 <- as.numeric(par3)
> par4 <- as.numeric(par4)
> par5 <- as.numeric(par5)
> if (par6 == 'White Noise') par6 <- 'white' else par6 <- 'ma'
> par7 <- as.numeric(par7)
> if (par8 != '') par8 <- as.numeric(par8)
> ox <- x
> if (par8 == '') {
+ if (par2 == 0) {
+ x <- log(x)
+ } else {
+ x <- (x ^ par2 - 1) / par2
+ }
+ } else {
+ x <- log(x,base=par8)
+ }
> if (par3 > 0) x <- diff(x,lag=1,difference=par3)
> if (par4 > 0) x <- diff(x,lag=par5,difference=par4)
> postscript(file="/var/wessaorg/rcomp/tmp/18lpg1445678338.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> op <- par(mfrow=c(2,1))
> plot(ox,type='l',main='Original Time Series',xlab='time',ylab='value')
> if (par8=='') {
+ mytitle <- paste('Working Time Series (lambda=',par2,', d=',par3,', D=',par4,')',sep='')
+ mysub <- paste('(lambda=',par2,', d=',par3,', D=',par4,', CI=', par7, ', CI type=',par6,')',sep='')
+ } else {
+ mytitle <- paste('Working Time Series (base=',par8,', d=',par3,', D=',par4,')',sep='')
+ mysub <- paste('(base=',par8,', d=',par3,', D=',par4,', CI=', par7, ', CI type=',par6,')',sep='')
+ }
> plot(x,type='l', main=mytitle,xlab='time',ylab='value')
> par(op)
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/2n8881445678338.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> racf <- acf(x, par1, main='Autocorrelation', xlab='time lag', ylab='ACF', ci.type=par6, ci=par7, sub=mysub)
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/3pjee1445678338.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> rpacf <- pacf(x,par1,main='Partial Autocorrelation',xlab='lags',ylab='PACF',sub=mysub)
> dev.off()
null device 
          1 
> (myacf <- c(racf$acf))
 [1]  1.000000e+00  1.177252e-02  1.004634e-01  2.690970e-01 -1.142587e-01
 [6] -6.777581e-02  1.944434e-02 -8.225227e-02 -4.451867e-02  5.030700e-02
[11] -7.959309e-05  3.008830e-03  2.259647e-01  2.459098e-02  1.859517e-02
[16]  6.865877e-02 -1.725411e-01 -2.033213e-01  1.820376e-02 -2.701034e-01
[21] -4.609652e-02 -5.807343e-03 -4.916297e-02  2.586773e-02  1.505015e-01
[26]  4.087856e-02  9.049091e-02 -5.705172e-02 -1.272795e-02 -6.366367e-02
[31] -1.059964e-01 -1.371086e-01 -1.118245e-01  6.498537e-02 -4.987277e-02
[36] -2.927578e-03  1.683741e-01  1.385023e-02  3.429755e-02 -6.156336e-02
[41] -6.215744e-02 -8.772499e-02 -5.362508e-02 -5.906059e-02 -9.255625e-02
[46] -3.115655e-02  4.819789e-02 -4.300916e-02  1.386130e-01
> (mypacf <- c(rpacf$acf))
 [1]  0.011772523  0.100338716  0.269603042 -0.133787134 -0.133751200
 [6] -0.028134613  0.009669180 -0.003948196  0.043811523  0.020952189
[11] -0.005223983  0.205478293  0.026165958 -0.033840958 -0.063560753
[16] -0.160436419 -0.195538961  0.068855449 -0.138868268  0.031791968
[21] -0.053365196  0.048378968 -0.004863810  0.114821857  0.024101363
[26]  0.063901934 -0.190145861  0.044360143  0.020989303 -0.027534225
[31] -0.104173062 -0.131677284  0.106457809  0.007038315 -0.031286044
[36] -0.020540188  0.032493070 -0.080771829 -0.099114522 -0.065061223
[41]  0.032354288  0.045987249  0.044100331 -0.100496749 -0.009995349
[46]  0.021831319 -0.027405422  0.023887242
> lengthx <- length(x)
> sqrtn <- sqrt(lengthx)
> 
> #Note: the /var/wessaorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/wessaorg/rcomp/createtable")
> 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Autocorrelation Function',4,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Time lag k',header=TRUE)
> a<-table.element(a,hyperlink('http://www.xycoon.com/basics.htm','ACF(k)','click here for more information about the Autocorrelation Function'),header=TRUE)
> a<-table.element(a,'T-STAT',header=TRUE)
> a<-table.element(a,'P-value',header=TRUE)
> a<-table.row.end(a)
> for (i in 2:(par1+1)) {
+ a<-table.row.start(a)
+ a<-table.element(a,i-1,header=TRUE)
+ a<-table.element(a,round(myacf[i],6))
+ mytstat <- myacf[i]*sqrtn
+ a<-table.element(a,round(mytstat,4))
+ a<-table.element(a,round(1-pt(abs(mytstat),lengthx),6))
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/4v9xr1445678338.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Partial Autocorrelation Function',4,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Time lag k',header=TRUE)
> a<-table.element(a,hyperlink('http://www.xycoon.com/basics.htm','PACF(k)','click here for more information about the Partial Autocorrelation Function'),header=TRUE)
> a<-table.element(a,'T-STAT',header=TRUE)
> a<-table.element(a,'P-value',header=TRUE)
> a<-table.row.end(a)
> for (i in 1:par1) {
+ a<-table.row.start(a)
+ a<-table.element(a,i,header=TRUE)
+ a<-table.element(a,round(mypacf[i],6))
+ mytstat <- mypacf[i]*sqrtn
+ a<-table.element(a,round(mytstat,4))
+ a<-table.element(a,round(1-pt(abs(mytstat),lengthx),6))
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/5zrca1445678338.tab") 
> 
> try(system("convert tmp/18lpg1445678338.ps tmp/18lpg1445678338.png",intern=TRUE))
character(0)
> try(system("convert tmp/2n8881445678338.ps tmp/2n8881445678338.png",intern=TRUE))
character(0)
> try(system("convert tmp/3pjee1445678338.ps tmp/3pjee1445678338.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.129   0.192   1.338